Organizations want to gain the benefits of DevOps – greater quality, improved stakeholder satisfaction, faster delivery, and higher productivity – across all aspects of IT, including their databases. In today's competitive business environment new solutions must be delivered in weeks, not months or years. Enhancements must be delivered in hours or days, not weeks or months. These delivery timeframes sound like fanciful thinking for traditional teams but are commonly achieved by teams following Disciplined Agile approaches. The good news is that proven techniques exist for data practitioners to work in a DevOps manner. The bad news is that many existing data practitioners don't know that these techniques exist, or if they do they don't know how to apply them in practice. This workshop introduces these Agile Data techniques and shows how they fit together in practice.
Very often people start with Scrum, but they quickly discover that to make Scrum work for databases it needs to be significantly extended to address the challenges associated with agile database evolution. These extensions include initial planning, initial requirements elicitation, initial architecture modeling, agile data modeling throughout construction, continuous database development, and streamlined deployment activities to name a few. The Disciplined Agile process decision framework has already done this extension work to address these challenges. Furthermore, because DA seamlessly supports both Scrum-based and continuous delivery strategies it is suitable for data practitioners new to agile as well as experienced teams looking to improve their approach. This workshop teaches you the techniques required for successful database evolution. An important aspect of this workshop is working through a data-specific case study.
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